Ortec Finance’s R&D Labs is a technical innovation center where we work and experiment with new IT techniques and concepts in order to research their applicability in finance. Together with students, academics and external parties we collaborate to design the future of financial decision-making.
R&D Labs is also our central ‘tech pillar’ that ensures that we take proper care of the tech side of things in everything we do at Ortec Finance. This includes major architectural decisions, assisting in the development of product increments, focusing on non-functional aspects, and organizing events to share knowledge.
Internships, theses and vacancies
We are looking for enthusiastic students and new employees to help us with our research projects and IT-solutions. If you are looking for a thesis topic, an internship or a position in our company, please have a look at our student assignments and vacancies.
Current focus areas
High Performance Computing
Ortec Finance delivers computational intensive simulation models that require a lot of data. There is an increasing need for speed. People desire real-time services while data volumes grow. At R&D Labs we work and experiment with cutting edge technologies in this field: GPU computing, manycore processors, and distributed programming models that use a serverless or container-based architecture.
As an expert provider of investment decision technology, we design user interfaces for our models that suit the user’s needs. We also focus on making them accessible to a non-expert user. Aside from this, we investigate alternatives to mouse & click interfaces and the potential added value of mixed reality on investment decision making.
We believe that the blockchain will have a serious impact on the financial world. At R&D Labs we aim to help to democratize the risk management for robotized financial services and contribute to its global standard. For example, by looking into the possibilities of smart contracts.
The field of machine learning is not widely used and accepted in the field of financial risk management (yet). Regulators often require a high level of economic interpretability on risk management models. Our current research is mainly focused around balancing the interpretability with model accuracy using econometric, statistical and machine learning tools.
Nowadays most of our clients prefer care-free SAAS solutions, that are hosted outside their premises. Applications run on private or hybrid clouds and often need to be connected to client user management systems. Security is key, for both the application software and the used infrastructure.
(Micro)Service Oriented Architecture
Markets and clients demand change, while technology makes it easier to combine the best components from multiple vendors into a holistic solution. In order to adapt quickly while maintaining our added value, we define core services that can be used in multiple solutions. Both in UI or API form, as a stand-alone product or as part of a broader solution.